Running and producing data from RAISHIN GRMHD simulations using a cluster

Here are the basic steps required in order to run and produce data for RAISHIN.

Setup your model carefully (pram.f90, mdgrmhd.f90 etc)
Run prepare.py to configure the appropriate number of cores and nodes for your MPI run. For example, prepare source for 2D, 512 cores, 24 cores/node:

prepare.py 2 512 24

Run toac.sh to send it to alphacrucis.
make and qsub mpirun.job to submit the job. Wait. Use status.sh once in a while to check the status of your simulation.
Once finished, copy the raw data files to the workstation where the visualization and analysis will be carried out
Run convert.py to convert the raw data files to VTK format

Name		Name	Last commit message	Last commit date
Latest commit History 11 Commits
scripts		scripts
Makefile		Makefile
Makefile_convert		Makefile_convert
Makefile_xgrmhd		Makefile_xgrmhd
README.md		README.md
Readme_GRMHD.txt		Readme_GRMHD.txt
bnd.f90		bnd.f90
calcha.f90		calcha.f90
calflx.f90		calflx.f90
calsf.f90		calsf.f90
caluu.f90		caluu.f90
cdtcfl.f90		cdtcfl.f90
convert.py		convert.py
convert_idl.f90		convert_idl.f90
convert_idl2.f90		convert_idl2.f90
convert_vtk2dn.f90		convert_vtk2dn.f90
convert_vtk2dn1.f90		convert_vtk2dn1.f90
convert_vtk2dn1d.f90		convert_vtk2dn1d.f90
convert_vtk3dn.f90		convert_vtk3dn.f90
convert_vtk3dn1.f90		convert_vtk3dn1.f90
coord.f90		coord.f90
correction.f90		correction.f90
ct.f90		ct.f90
func.f90		func.f90
grfunc.f90		grfunc.f90
grid.f90		grid.f90
hll.f90		hll.f90
main.f90		main.f90
mdgrmhd.f90		mdgrmhd.f90
mpirun.job		mpirun.job
mpisub.f90		mpisub.f90
physfunc.f90		physfunc.f90
pram.f90		pram.f90
pram_2Dmagtrs.f90		pram_2Dmagtrs.f90
pram_3Dtorus.f90		pram_3Dtorus.f90
prepare.py		prepare.py
rec.f90		rec.f90
recov.f90		recov.f90
restar.f90		restar.f90
rkt.f90		rkt.f90
run.py		run.py
status.sh		status.sh
toac.sh		toac.sh

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